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A novel discrete fractional Gronwall-type inequality and its application in pointwise-in-time error estimates Journal article
Li, D. F., She, M.F., Sun, H. W., Yan, X.Q.. A novel discrete fractional Gronwall-type inequality and its application in pointwise-in-time error estimates[J]. Journal of Scientific Computing, 2022, 91(1), 1-27.
Authors:  Li, D. F.;  She, M.F.;  Sun, H. W.;  Yan, X.Q.
Favorite | TC[WOS]:8 TC[Scopus]:8 | Submit date：2022/07/25
Nonlinear Time-fractional Equations  High-order Time-stepping Methods  Modified Grönwall Inequality  Pointwise-in-time Error Estimates  
A novel $L1$ method for solving the multi-term time-fractional diffusion problem Journal article
She, M. F., Li, D. F., Sun, H. W.. A novel $L1$ method for solving the multi-term time-fractional diffusion problem[J]. Mathematics and Computers in Simulation, 2022, 584-606.
Authors:  She, M. F.;  Li, D. F.;  Sun, H. W.
Favorite | TC[WOS]:21 TC[Scopus]:21  IF:4.4/3.6 | Submit date：2022/07/25
Multi-term Time-fractional Equation  Modified L1 Scheme  Chebyshev–galerkin Spectral Method  Error Estimates  
Intelligent Nanomesh-Reinforced Graphene Pressure Sensor with Ultra Large Linear Range Journal article
Qiao, Y., Jian, J., Tang, H., Ji, S., Liu, Y., Liu, H., Li, Y., Li, X., Han, F., Liu, Z., Cui, T., Gou, G., Jiang, L., Yang, Y., Zhou, B., Ren, T., Zhou, J.. Intelligent Nanomesh-Reinforced Graphene Pressure Sensor with Ultra Large Linear Range[J]. Journal of Materials Chemistry A, 2022, N/A-N/A.
Authors:  Qiao, Y.;  Jian, J.;  Tang, H.;  Ji, S.;  Liu, Y.; et al.
Favorite | TC[WOS]:25  | Submit date：2022/07/27
Pressure Sensor  
Comparative genomics provides insights into the aquatic adaptations of mammals Journal article
Yuan, Yuan, Zhang, Yaolei, Zhang, Peijun, Liu, Chang, Wang, Jiahao, Gao, Haiyu, Rus Hoelzel, A., Seim, Inge, Lv, Meiqi, Lin, Mingli, Dong, Lijun, Gao, Haoyang, Yang, Zixin, Caruso, Francesco, Lin, Wenzhi, Da Fonseca, Rute R., Wang, Ding, Wang, Xianyan, Rasmussen, Marianne H., Liu, Mingming, Zheng, Jinsong, Zhao, Liyuan, Campos, Paula F., Kang, Hui, Iversen, Maria, Song, Yue, Guo, Xinyu, Guo, Jiao, Qin, Yating, Pan, Shanshan, Xu, Qiwu, Meng, Lingfeng, Yunga, A., Liu, Shanshan, Ming-Yuen Lee, Simon, Liu, Xin, Xu, Xun, Yang, Huanming, Fan, Guangyi, Wang, Kun, Li, Songhai. Comparative genomics provides insights into the aquatic adaptations of mammals[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2021, 118(37), e2106080118.
Authors:  Yuan, Yuan;  Zhang, Yaolei;  Zhang, Peijun;  Liu, Chang;  Wang, Jiahao; et al.
Favorite | TC[WOS]:58 TC[Scopus]:57  IF:9.4/10.8 | Submit date：2021/12/08
Aquatic Adaptation  Comparative Genomics  Marine Mammals  
Accelerating precision anti-cancer therapy by time-lapse and label-free 3D tumor slice culture platform Journal article
Xing, F., Huang, S., Liu, Y.-C., Lyu, X., Su, S. M., Chan, U. I., Wu, P.-C., Yan, Y., Ai, N., Li, J., Zhao, M., Rajendran, B., Liu, J., Shao, F., Sun, H., Luo, G., Zhu, W., Miao, K., Zhao, Q., Luo, KQ., Ge, W., Xu, X., Wang, G., Liu, T.-M., Deng, C.-X.. Accelerating precision anti-cancer therapy by time-lapse and label-free 3D tumor slice culture platform[J]. Theranostics, 2021, 9415-9430.
Authors:  Xing, F.;  Huang, S.;  Liu, Y.-C.;  Lyu, X.;  Su, S. M.; et al.
Favorite |   IF:12.4/12.0 | Submit date：2022/08/26
Tumor Organoid  Lipofuscin  Two-photon Fluorescence Microscopy  
Tailoring large magnetoresistance in Dirac semimetal SrIrO3 films Journal article
Ren, Z. Y., Miao, Jun, Zhang, L. P., Lv, Z. L., Cao, J. P., Jakob, Gerhard, Zhou, Jing, Chen, J. K., Meng, K. K., Li, H. F., Jiang, Y.. Tailoring large magnetoresistance in Dirac semimetal SrIrO3 films[J]. APPLIED PHYSICS LETTERS, 2021, 119(11), 112402.
Authors:  Ren, Z. Y.;  Miao, Jun;  Zhang, L. P.;  Lv, Z. L.;  Cao, J. P.; et al.
Favorite | TC[WOS]:3 TC[Scopus]:2  IF:3.5/3.5 | Submit date：2021/10/02
Magnetoresistance  Dirac Semimetal  
A 50.4 GOPs/W FPGA-Based MobileNetV2 Accelerator using the Double-Layer MAC and DSP Efficiency Enhancemen Conference paper
Li, J., Chen, J., Un, K. F., Yu, W. H., Mak, P. I., Martins, R. P.. A 50.4 GOPs/W FPGA-Based MobileNetV2 Accelerator using the Double-Layer MAC and DSP Efficiency Enhancemen[C], IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2021.
Authors:  Li, J.;  Chen, J.;  Un, K. F.;  Yu, W. H.;  Mak, P. I.; et al.
Favorite | TC[WOS]:2  | Submit date：2022/01/25
Computation Efficiency  Convolutional Neural Network (Cnn)  Fpga  Object Recognition  Reconfigurability  
[Fe(CN)6] vacancy-boosting oxygen evolution activity of Co-based Prussian blue analogues for hybrid sodium-air battery Journal article
Kang, Y., Wang, S., Hui, K. S., Li, H. F., Liang, F., Wu, X. L., Zhang, Q., Zhou, W., Chen, L., Chen, F., Hui, K. N.. [Fe(CN)6] vacancy-boosting oxygen evolution activity of Co-based Prussian blue analogues for hybrid sodium-air battery[J]. Materials Today Energy, 2021, 20, 100572.
Authors:  Kang, Y.;  Wang, S.;  Hui, K. S.;  Li, H. F.;  Liang, F.; et al.
Favorite | TC[WOS]:39 TC[Scopus]:42  IF:9.0/8.4 | Submit date：2021/09/10
Aqueous Sodium-air Battery  Oxygen Evolution Reaction  Surface Electronic Configuration  [Fe(Cn)6] Vacancies  
[Fe(CN)6] Vacancy Boosting Oxygen Evolution Activity of Co-based Prussian Blue Analogues for Hybrid Sodium-air Battery Journal article
Kang, Y., Wang, S., Hui, K.S., Li, H., Liang, F., Wu, X.L., Zhang, Q.J., Zhou, W., Chen, L., Chen, F.M., Hui, K. N.. [Fe(CN)6] Vacancy Boosting Oxygen Evolution Activity of Co-based Prussian Blue Analogues for Hybrid Sodium-air Battery[J]. Materials Today Energy, 2021, 20, 100572.
Authors:  Kang, Y.;  Wang, S.;  Hui, K.S.;  Li, H.;  Liang, F.; et al.
Favorite | TC[WOS]:39 TC[Scopus]:42  IF:9.0/8.4 | Submit date：2022/08/11
Oxygen Evolution Reaction  [Fe(Cn)6] Vacancies  Surface Electronic Configuration  Aqueous Sodium-air Battery  
GraphLSHC: Towards large scale spectral hypergraph clustering Journal article
Yang, Y. Y., Deng, S. C., Lu, J., Li, Y. H., Gong, Z. G., U, L. H., Hao, Z. F.. GraphLSHC: Towards large scale spectral hypergraph clustering[J]. Information Sciences, 2021, 117-134.
Authors:  Yang, Y. Y.;  Deng, S. C.;  Lu, J.;  Li, Y. H.;  Gong, Z. G.; et al.
Favorite |   IF:0/0 | Submit date：2022/08/26
Machine Learningunsupervised Learningclusteringhypergraph